cMDS math
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Gram matrix Spectral Decomposition
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c310eaf447aa0a9b3dbb762e22d1bd1b98d89bab: Frobenius Norm
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When X is known, projecting N points with top p PCs achieved from its covariance matrix in Principal Component Analysis (PCA) leads to the same embedding results as cMDS (up to an arbitrary rotation). (since covariance matrix and gram matrix share eigenvalues)
Proportion of Variance can be used to find optimum intrinsic dimensionality